Stand Up a Data Platform for a Mobility-Data Startup's First ML Model
Overview
What this challenge is about.
Build a streaming data pipeline and feature store for a mobility startup’s first ML model. Earn a verifiable certificate.
The scenario
The startup (around 28 staff, around 12,000 active vehicles instrumented) has been training models on hand-pulled CSVs and is finally building real data infra to support its growth into automotive-OEM customers.
The Brief
What you'll do, and what you'll demonstrate.
Stand up a working data platform slice (streaming + batch + feature store + training job) for a mobility-data startup's first ML model.
Earning criteria — what you'll demonstrate
- Design a data platform across streaming, batch, and feature serving layers
- Implement infrastructure-as-code for reproducible environments
- Operate a feature store as the contract between data and ML
- Hand off a platform with documentation that survives without you
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
AI Software Engineering Group Project
Master · Capstone
Strong alignment
This challenge maps to AI Software Engineering Group Project at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Data Engineering
Design and build pipelines that collect, transform, and deliver reliable data at scale.
- Streaming Ingestion
Apply streaming ingestion to solve real industry problems and demonstrate production-level capability.
- Feature Store
Apply feature store to solve real industry problems and demonstrate production-level capability.
- Infrastructure As Code
Apply infrastructure as code to solve real industry problems and demonstrate production-level capability.
- Ci Cd
Apply ci cd to solve real industry problems and demonstrate production-level capability.
- Team Collaboration
Apply team collaboration to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
MLOps Engineer
Infrastructure-as-code plus feature-store contracts are bread-and-butter MLOps responsibilities.
This challenge sharpens
- infrastructure-as-code
- feature-store
- ci-cd
Machine Learning Engineer
Wiring a sample training job into the platform mirrors the MLE's daily integration work.
This challenge sharpens
- feature-store
- ci-cd
- team-collaboration